In contact centers today, there is an increasing need for contact center supervisors to monitor the performance of agents in real time. This can be important not only to ensure that selected sets of customer contacts (e.g., gold, silver, and bronze customers) are receiving an appropriate level of service but also to reward and discipline agents based on their performance and to evaluate agent staffing needs by skill/split at any point during the day.
To provide such monitoring, there are many products on the market including Operational Analyst™ and Call Management System™ by Avaya, Inc. To effectively monitor the contact center, these products must track a myriad of cumulative data objects, including the number of contacts handled by each agent, the amount of time required by each agent to service a contact, the wait time for sets of enqueued contacts and for individual contacts, and the like. A “cumulative datum” is a sum that grows and/or stays the same in magnitude over a selected measurement (e.g., time) interval; it commonly does not decrease in magnitude over the interval. Real time monitoring of these objects is made difficult by the limited memory available to store real time event information.
To accommodate the limited memory and provide some level of meaningful object tracking, “ratcheting” is widely used by contact centers management systems to control the magnitude of cumulative data. Referring to FIG. 4, the basic measures are monitored continuously and reset to zero at each 30-minute time interval. In the next successive interval, the measure restarts the count from zero. In this way, the cumulative datum is converted into a series of summary measurements at fixed intervals of time.
Ratcheting can have a number of problems.
First, after being reset to zero following each measured time interval there is effectively no measurement available to administrators until additional events have been counted. This practice has been likened by administrators to piloting an airplane in which all of the instruments are periodically reset to zero. Administrators feel like they are flying blind until the real-time data begins to increase in magnitude.
Second, the problem above is magnified whenever the ratio of two cumulative measures is being computed in real time. For example, if the administrator wants to monitor the average time agents are talking on a call that would be the ratio of cumulative talk time (numerator) to the cumulative number of calls (denominator). But ratcheting resets both the numerator and denominator to zero periodically so (a) the ratio cannot even be computed until the denominator becomes non zero and (b) the ratio fluctuates wildly until both numerator and denominator accumulate sufficient counts to be representative. These spurious fluctuations severely limit the ability to set meaningful thresholds for automatic triggering of notifications or corrective actions.
It would be desirable to provide to administrators the magnitude of the measured cumulative datum in a rolling window of time rather than since the datum was last reset to zero. For example, where the measured object is the number of answered phone calls it would be valuable to know not only the number of calls answered since the most recent half hour boundary but also the number of calls answered in the last thirty minutes.